LLM Summarization Chain Example

Hello there! 👋 Welcome to this exciting example of using LangChain with Go to create a summarization chain powered by a Large Language Model (LLM)!

What does this example do?

This nifty little program demonstrates how to use the LangChain Go library to create a summarization chain. Here's what it does in a nutshell:

1. Sets up a connection to Google's Vertex AI (a powerful LLM service)
2. Creates a summarization chain using the LLM
3. Loads a sample text about AI and large language models
4. Splits the text into manageable chunks
5. Feeds the text chunks into the summarization chain
6. Outputs a concise summary of the input text

The cool parts

• Uses the vertex package to connect to Google's Vertex AI
• Demonstrates the chains.LoadRefineSummarization function to create a summarization chain
• Shows how to use documentloaders and textsplitter to prepare input text
• Illustrates calling the chain with chains.Call and extracting the result

Running the example

To run this example, make sure you have the necessary credentials set up for Google Vertex AI. Then, simply execute the Go file:

go run llm_summarization_example.go

You'll see a neat summary of the input text about large language models printed to your console!

Why is this useful?

This example showcases how easy it is to create powerful AI-driven applications using LangChain and Go. Summarization is just one of many tasks you can accomplish with LLMs. The techniques demonstrated here can be adapted for various other AI-powered text processing tasks.

Happy coding, and have fun exploring the world of AI with Go and LangChain! 🚀🤖